Ecological risk assessment of commonly used antibiotics in aquatic ecosystems along the coast of China

文献类型： 外文期刊

第一作者： Zhou, Xuan

作者： Zhou, Xuan;Shi, Yajuan;Song, Shuai;Qian, Li;Xu, Qiuyun;Shao, Xiuqing;Li, Xuan;Zhou, Xuan;Shi, Yajuan;Song, Shuai;Qian, Li;Xu, Qiuyun;Shao, Xiuqing;Li, Xuan;Lu, Yonglong;Lu, Yonglong;Lu, Yonglong;Wang, Chenchen;Wu, Yanqi;Liang, Ruoyu

作者机构：

关键词： Antibiotics; Ecological risk assessment; ICE model; Species sensitivity distribution

期刊名称：SCIENCE OF THE TOTAL ENVIRONMENT （ 影响因子：8.2； 五年影响因子：8.6 ）

ISSN： 0048-9697

年卷期： 2024 年 935 卷

页码：

收录情况： SCI

摘要： The consistent input of antibiotics into aquatic environments may pose risks to various creatures and ecosystems. However, risk assessment of pharmaceuticals and personal care products (PPCPs) in aquatic environments is frequently limited by the lack of toxicity data. To investigate the risk of commonly used antibiotics to various aquatic creatures, we focused on the distribution patterns and temporal dynamics of antibiotics in the coastal estuary area of China and performed a comprehensive ecological risk assessment for four antibiotics: erythromycin (ERY), tetracycline (TCN), norfloxacin (NOR) and sulfamethoxazole (SMX). An interspecies correlation estimation (ICE) -species sensitivity distribution (SSD) combined model was applied to predict the toxicity data of untested aquatic species, and an accurate ecological risk assessment procedure was developed to evaluate the risk level of PPCPs. The results of risk quotient assessments and probabilistic risk assessments (PRAs) suggested that four objective antibiotics in the Chinese coastal estuary area were at a low risk level. These antibiotics posed a high risk in antibiotic -related global hot spots, with probabilistic risk values for ERY, NOR, SMX, and TCN of 81.33 %, 27.08 %, 21.13 %, and 15.44 %, respectively. We applied an extrapolation method to overcome the lack of toxicity data in ecological risk assessment, enhanced the ecological reality of water quality criteria derivation and reduced the uncertainty of risk assessment for antibiotics.

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